AIMC Topic: Neural Networks, Computer

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Ensemble Deep Learning for Biomedical Time Series Classification.

Computational intelligence and neuroscience
Ensemble learning has been proved to improve the generalization ability effectively in both theory and practice. In this paper, we briefly outline the current status of research on it first. Then, a new deep neural network-based ensemble method that ...

Delay-distribution-dependent H state estimation for delayed neural networks with (x,v)-dependent noises and fading channels.

Neural networks : the official journal of the International Neural Network Society
This paper deals with the H state estimation problem for a class of discrete-time neural networks with stochastic delays subject to state- and disturbance-dependent noises (also called (x,v)-dependent noises) and fading channels. The time-varying sto...

Tracking and simulating dynamics of implicit stereotypes: A situated social cognition perspective.

Journal of personality and social psychology
Adopting a situated social cognition perspective, we relied on different methodologies-1 computational and 3 empirical studies-to investigate social group-related specificities pertaining to implicit gender-domain stereotypes, as measured by a mouse-...

Emotional states recognition, implementing a low computational complexity strategy.

Health informatics journal
This article describes a methodology to recognize emotional states through an electroencephalography signals analysis, developed with the premise of reducing the computational burden that is associated with it, implementing a strategy that reduces th...

Efficient Descriptor-Based Segmentation of Parotid Glands With Nonlocal Means.

IEEE transactions on bio-medical engineering
OBJECTIVE: We introduce descriptor-based segmentation that extends existing patch-based methods by combining intensities, features, and location information. Since it is unclear which image features are best suited for patch selection, we perform a b...

Deep Neural Networks for Identifying Cough Sounds.

IEEE transactions on biomedical circuits and systems
In this paper, we consider two different approaches of using deep neural networks for cough detection. The cough detection task is cast as a visual recognition problem and as a sequence-to-sequence labeling problem. A convolutional neural network and...

Reduction strategies for hierarchical multi-label classification in protein function prediction.

BMC bioinformatics
BACKGROUND: Hierarchical Multi-Label Classification is a classification task where the classes to be predicted are hierarchically organized. Each instance can be assigned to classes belonging to more than one path in the hierarchy. This scenario is t...

Predictive time-series modeling using artificial neural networks for Linac beam symmetry: an empirical study.

Annals of the New York Academy of Sciences
Over half of cancer patients receive radiotherapy (RT) as partial or full cancer treatment. Daily quality assurance (QA) of RT in cancer treatment closely monitors the performance of the medical linear accelerator (Linac) and is critical for continuo...

Predicting ventriculoperitoneal shunt infection in children with hydrocephalus using artificial neural network.

Child's nervous system : ChNS : official journal of the International Society for Pediatric Neurosurgery
OBJECTIVES: The relationships between shunt infection and predictive factors have not been previously investigated using Artificial Neural Network (ANN) model. The aim of this study was to develop an ANN model to predict shunt infection in a group of...

Emergence of event cascades in inhomogeneous networks.

Scientific reports
There is a commonality among contagious diseases, tweets, and neuronal firings that past events facilitate the future occurrence of events. The spread of events has been extensively studied such that the systems exhibit catastrophic chain reactions i...